Bayesian Model

Game theory and brain strategies [2023-01-23] Atelier jeu et cerveau https://laurentperrinet.github.io/talk/2023-01-23-game-theory-and-the-brain Only the speaker can read these notes Press S key to view Photo by Naser Tamimi on Unsplash https://unsplash.com/fr/photos/yG9pCqSOrAg Game theory and brain strategies Le jeu du cerveau et du hasard, The Conversation

[2022-11-21] Alex Reynaud’s lab meeting https://laurentperrinet.github.io/slides/2022-11-21_flash-lag-effect Only the speaker can read these notes Press S key to view Timing in the visual pathways Ultra-rapid visual processing (see review). Compensating visual delays (Perrinet, Adams & Friston 2014).

Within the central nervous system, visual areas are essential in transforming the raw luminous signal into a representation which …

A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on …

Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving …

see a write-up in “Humans adapt their anticipatory eye movements to the volatility of visual motion properties”

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. …

As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …

see Kaplan and al, 2014

Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed …

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the …

Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).

This paper introduces a model of oculomotor control during the smooth pursuit of occluded visual targets. This model is based upon …

Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed …

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent …

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent …

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent …

If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate …

Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …

Accuracy in estimating an object’s global motion over time is not only affected by the noise in visual motion information but …

Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …

see this more recent talk @ UCL, London

Based on Laurent U Perrinet, Guillaume S Masson (2012). Motion-based prediction is sufficient to solve the aperture problem. Neural Computation. PDF Cite Pdf arXiv see follow-up on motion extrapolation: Mina A Khoei, Guillaume S Masson, Laurent U Perrinet (2013).

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual …

Short presentation of a large moving pattern elicits an Ocular Following Response (OFR) that exhibits many of the properties attributed …

Integrating information is essential to measure the physical 2D motion of a surface from both ambiguous local 1D motion of its …

The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following …

The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following …

The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …

The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in Ocular Following …

Perceptual and oculomotor data demonstrate that, when the visual information about an object’s motion differs on the local …

The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …

The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …

The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …

The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by …

A goal of low-level neural processes is to build an efficient code extracting the relevant information from the sensory input. It is …